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Proposed Enhancement algorithm for Company Employers Management using Genetic Algorithm in Data Mining | ||
| Engineering and Technology Journal | ||
| Article 1, Volume 28, Issue 2, 2010, Pages 261-270 PDF (196.12 K) | ||
| DOI: 10.30684/etj.28.2.4 | ||
| Author | ||
| Dalia Nabeel Kamal | ||
| Abstract | ||
| Data mining is a process of automatically discovering useful information in large data repositories that uses a variety of data analysis tools to discover patterns and relationships that can be hidden among vast amount of data. From these patterns and relationships, businesses and organizations can make valid predictions about future trends in all areas of business. Association rule mining is a typical approach used in data mining domain for uncovering interesting trends, patterns and rules in large datasets. This research concentrates on one particular aspect to improve the efficiency of the association rules technique in data mining and implement the proposed algorithm on employers management system. The resulted association which introduced by applying rule technique, will be treated by genetic algorithm to find a new rules that might be more efficient and powerful for proposed data base by propose cross point ,threshold for fitness to deal consistently with the formula of the association rules, and gives good results. | ||
| Keywords | ||
| Association Rules; frequent item sets; closed frequent item sets and maximal frequent item sets | ||
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